6 citations · 11 across the 6 of their papers we have counts for
4 papers · 1 filter
Large Language Models for Disease Diagnosis: A Scoping Review
Shuang Zhou, Zidu Xu, Mian Zhang +14
Automatic disease diagnosis has become increasingly valuable in clinical practice. The advent of large language models (LLMs) has catalyzed a paradigm shift in artificial intellige…
GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models
Yi Fang, Dongzhe Fan, Daochen Zha +1
This work studies self-supervised graph learning for text-attributed graphs (TAGs) where nodes are represented by textual attributes. Unlike traditional graph contrastive methods t…
GraphFM: A Comprehensive Benchmark for Graph Foundation Model
Yuhao Xu, Xinqi Liu, Keyu Duan +4
Foundation Models (FMs) serve as a general class for the development of artificial intelligence systems, offering broad potential for generalization across a spectrum of downstream…
UniGLM: Training One Unified Language Model for Text-Attributed Graph Embedding
Yi Fang, Dongzhe Fan, Sirui Ding +2
Representation learning on text-attributed graphs (TAGs), where nodes are represented by textual descriptions, is crucial for textual and relational knowledge systems and recommend…